29 citations · 44 across the 17 of their papers we have counts for
18 papers
Tokenomics: Quantifying Where Tokens Are Used in Agentic Software Engineering
Mohamad Salim, Jasmine Latendresse, SayedHassan Khatoonabadi +1
LLM-based Multi-Agent (LLM-MA) systems are increasingly applied to automate complex software engineering tasks such as requirements engineering, code generation, and testing. Howev…
Evaluating the Use of LLMs for Automated DOM-Level Resolution of Web Performance Issues
Gideon Peters, SayedHassan Khatoonabadi, Emad Shihab
Users demand fast, seamless webpage experiences, yet developers often struggle to meet these expectations within tight constraints. Performance optimization, while critical, is a t…
Beyond Synthetic Benchmarks: Evaluating LLM Performance on Real-World Class-Level Code Generation
Musfiqur Rahman, SayedHassan Khatoonabadi, Emad Shihab
Large language models (LLMs) have demonstrated strong performance on function-level code generation benchmarks, yet real-world software development increasingly demands class-level…
Automated File-Level Logging Generation for Machine Learning Applications using LLMs: A Case Study using GPT-4o Mini
Mayra Sofia Ruiz Rodriguez, SayedHassan Khatoonabadi, Emad Shihab
Logging is essential in software development, helping developers monitor system behavior and aiding in debugging applications. Given the ability of large language models (LLMs) to…
The Impact of Large Language Models (LLMs) on Code Review Process
Antonio Collante, Samuel Abedu, SayedHassan Khatoonabadi +3
Large language models (LLMs) have recently gained prominence in the field of software development, significantly boosting productivity and simplifying teamwork. Although prior stud…
How Robust are LLM-Generated Library Imports? An Empirical Study using Stack Overflow
Jasmine Latendresse, SayedHassan Khatoonabadi, Emad Shihab
Software libraries are central to the functionality, security, and maintainability of modern code. As developers increasingly turn to Large Language Models (LLMs) to assist with pr…
Evaluating the Use of LLMs for Documentation to Code Traceability
Ebube Alor, SayedHassan Khatoonabadi, Emad Shihab
Large Language Models (LLMs) offer new potential for automating documentation-to-code traceability, yet their capabilities remain underexplored. We present a comprehensive evaluati…
OpenClassGen: A Large-Scale Corpus of Real-World Python Classes for LLM Research
Musfiqur Rahman, SayedHassan Khatoonabadi, Emad Shihab
Existing class-level code generation datasets are either synthetic (ClassEval: 100 classes) or insufficient in scale for modern training needs (RealClassEval: 400 classes), hinderi…
Synergizing LLMs and Knowledge Graphs: A Novel Approach to Software Repository-Related Question Answering
Samuel Abedu, SayedHassan Khatoonabadi, Emad Shihab
Software repositories contain valuable information for understanding the development process. However, extracting insights from repository data is time-consuming and requires techn…
An Approach for Auto Generation of Labeling Functions for Software Engineering Chatbots
Ebube Alor, Ahmad Abdellatif, SayedHassan Khatoonabadi +1
Software engineering (SE) chatbots are increasingly gaining attention for their role in enhancing development processes. At the core of chatbots are Natural Language Understanding…
Automatic Detection of LLM-Generated Code: A Comparative Case Study of Contemporary Models Across Function and Class Granularities
Musfiqur Rahman, SayedHassan Khatoonabadi, Ahmad Abdellatif +1
The adoption of Large Language Models (LLMs) for code generation risks incorporating vulnerable code into software systems. Existing detectors face two critical limitations: a lack…
Is ChatGPT a Good Software Librarian? An Exploratory Study on the Use of ChatGPT for Software Library Recommendations
Jasmine Latendresse, SayedHassan Khatoonabadi, Ahmad Abdellatif +1
Software libraries play a critical role in the functionality, efficiency, and maintainability of software systems. As developers increasingly rely on Large Language Models (LLMs) t…
The Impact of Environment Configurations on the Stability of AI-Enabled Systems
Musfiqur Rahman, SayedHassan Khatoonabadi, Ahmad Abdellatif +2
Nowadays, software systems tend to include Artificial Intelligence (AI) components. Changes in the operational environment have been known to negatively impact the stability of AI-…
Predicting the First Response Latency of Maintainers and Contributors in Pull Requests
SayedHassan Khatoonabadi, Ahmad Abdellatif, Diego Elias Costa +1
The success of a Pull Request (PR) depends on the responsiveness of the maintainers and the contributor during the review process. Being aware of the expected waiting times can lea…
Understanding the Helpfulness of Stale Bot for Pull-based Development: An Empirical Study of 20 Large Open-Source Projects
SayedHassan Khatoonabadi, Diego Elias Costa, Suhaib Mujahid +1
Pull Requests (PRs) that are neither progressed nor resolved clutter the list of PRs, making it difficult for the maintainers to manage and prioritize unresolved PRs. To automatica…
On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests
SayedHassan Khatoonabadi, Diego Elias Costa, Rabe Abdalkareem +1
Pull-based development has enabled numerous volunteers to contribute to open-source projects with fewer barriers. Nevertheless, a considerable amount of pull requests (PRs) with va…
GAP2WSS: A Genetic Algorithm based on the Pareto Principle for Web Service Selection
SayedHassan Khatoonabadi, Shahriar Lotfi, Ayaz Isazadeh
Despite all the progress in Web service selection, the need for an approach with a better optimality and performance still remains. This paper presents a genetic algorithm by adopt…
Compressed-domain visual saliency models: A comparative study
Sayed Hossein Khatoonabadi, Ivan V. Bajic, Yufeng Shan
Computational modeling of visual saliency has become an important research problem in recent years, with applications in video quality estimation, video compression, object trackin…